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How Many Are at Increased Risk of Severe COVID-19 Disease? Rapid Global, Regional and National Estimates for 2020

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How Many Are at Increased Risk of Severe COVID-19 Disease? Rapid Global, Regional and National Estimates for 2020 medRxiv preprint doi: https://doi.org/10.1101/2020.04.18.20064774; this version posted April 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . How many are at increased risk of severe COVID-19 disease? Rapid global, regional and national estimates for 2020 Andrew Clark1, Mark Jit,2 Charlotte Warren-Gash,3 Bruce Guthrie,4 Harry HX Wang,5 Stewart W Mercer,4 Colin Sanderson,1 Martin McKee,1 Christopher Troeger,6 Kanyin I Ong,6 Francesco Checchi,2 Pablo Perel,3 Sarah Joseph,7 Hamish P Gibbs,2 Amitava Banerjee8, CMMID COVID-19 working group,9 Rosalind M Eggo2 1Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, Tavistock Place, WC1H 9SH 2Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT 3Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT 4Centre for Population Health Sciences, Usher Institute, University of Edinburgh, Old Medical School, Teviot Place, EH8 9AG 5School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, PR China 6University of Washington, Seattle WA, USA 7IAVI Human Immunology Laboratory, Imperial College London 8Institute of Health Informatics, University College London, London 9Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street. WC1E 7HT UK The LSHTM CMMID COVID-19 working group is (ordered randomly): Emily S Nightingale, Kathleen O'Reilly, Thibaut Jombart, W John Edmunds, Alicia Rosello, Fiona Yueqian Sun, Katherine E. Atkins, Nikos I Bosse, Samuel Clifford, Timothy W Russell, Arminder K Deol, Yang Liu, Simon R Procter, Quentin J Leclerc, Graham Medley, Gwen Knight, James D Munday, Adam J Kucharski, Carl A B Pearson, Petra Klepac, Kiesha Prem, Rein M G J Houben, Akira Endo, Stefan Flasche, Nicholas G. Davies, Charlie Diamond, Kevin van Zandvoort, Sebastian Funk, Megan Auzenbergs, Eleanor M Rees, Damien C Tully, Jon C Emery, Billy J Quilty, Sam Abbott, Julian Villabona-Arenas, Stéphane Hué, Joel Hellewell, Amy Gimma, Christopher I Jarvis Correspondence to: [email protected] Competing Interest Statement The authors have declared no competing interest. NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2020.04.18.20064774; this version posted April 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . Funding Statement We acknowledge the following for funding: RME: HDR UK (grant: MR/S003975/1), MRC (grant: MC_PC 19065); HPG: This research is funded by the Department of Health and Social Care using UK Aid funding and is managed by the NIHR. The views expressed in this publication are those of the author(s) and not necessarily those of the Department of Health and SocialCare (grant code: ITCRZ 03010); CWG: Wellcome Intermediate Clinical Fellowship (201440_Z_16_Z). 2 medRxiv preprint doi: https://doi.org/10.1101/2020.04.18.20064774; this version posted April 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . Background The risk of severe COVID-19 disease is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 illness, and how this varies between countries may inform the design of possible strategies to shield those at highest risk. Methods We estimated the number of individuals at increased risk of severe COVID-19 disease by age (5-year age groups), sex and country (n=188) based on prevalence data from the Global Burden of Disease (GBD) study for 2017 and United Nations population estimates for 2020. We also calculated the number of individuals without an underlying condition that could be considered at-risk because of their age, using thresholds from 50-70 years. The list of underlying conditions relevant to COVID-19 disease was determined by mapping conditions listed in GBD to the guidelines published by WHO and public health agencies in the UK and US. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. Results We estimate that 1.7 (1.0 - 2.4) billion individuals (22% [15-28%] of the global population) are at increased risk of severe COVID-19 disease. The share of the population at increased risk ranges from 16% in Africa to 31% in Europe. Chronic kidney disease (CKD), cardiovascular disease (CVD), diabetes and chronic respiratory disease (CRD) were the most prevalent conditions in males and females aged 50+ years. African countries with a high prevalence of HIV/AIDS and Island countries with a high prevalence of diabetes, also had a high share of the population at increased risk. The prevalence of multimorbidity (>1 underlying conditions) was three times higher in Europe than in Africa (10% vs 3%). Conclusion Based on current guidelines and prevalence data from GBD, we estimate that one in five individuals worldwide has a condition that is on the list of those at increased risk of severe COVID-19 disease. However, for many of these individuals the underlying condition will be undiagnosed or not severe enough to be captured in health systems, and in some cases the increase in risk may be quite modest. There is an urgent need for robust analyses of the risks associated with different underlying conditions so that countries can identify the highest risk groups and develop targeted shielding policies to mitigate the effects of the COVID-19 pandemic. 3 medRxiv preprint doi: https://doi.org/10.1101/2020.04.18.20064774; this version posted April 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . Research in context Evidence before this study As the COVID-19 pandemic evolves, countries are considering policies of ‘shielding’ the most vulnerable, but there is currently very limited evidence on the number of individuals that might need to be shielded. Guidelines on who is currently believed to be at increased risk of severe COVID-19 illness have been published online by the WHO and public health agencies in the UK and US. We searched PubMed ("Risk factors" AND "COVID-19") without language restrictions, from database inception until April 5, 2020, and identified 62 studies published between Feb 15, 2020 and March 20, 2020. Evidence from China, Italy and the USA indicates that older individuals, males and those with underlying conditions, such as CVD, diabetes and CRD, are at greater risk of severe COVID-19 illness and death. Added value of this study This study combines evidence from large international databases and new analysis of large multimorbidity studies to inform policymakers about the number of individuals that may be at increased risk of severe COVID-19 illness in different countries. We developed a tool for rapid assessments of the number and percentage of country populations that would need to be targeted under different shielding policies. Implications of all the available evidence Quantifying how many and who is at increased risk of severe COVID-19 illness is critical to help countries design more effective interventions to protect vulnerable individuals and reduce pressure on health systems. This information can also inform a broader assessment of the health, social and economic implications of shielding various groups. 4 medRxiv preprint doi: https://doi.org/10.1101/2020.04.18.20064774; this version posted April 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . Introduction Emerging evidence from China, Europe and the USA has shown a consistently higher risk of severe COVID-19 disease in older individuals and those with underlying health conditions.1-3 Mild and moderate cases are those with symptoms but without evidence of pneumonia or dyspnea, and low mortality is expected in this group. Severe cases have those symptoms, would require hospitalisation if available, and are at risk of increased mortality.4,5 In a recent report from the USA, underlying conditions were reported in 71% (732/1037) of individuals hospitalised with COVID-19 and 94% (173/184) of deaths.1 The World Health Organization (WHO) as well as public health agencies in countries including the UK and US, have issued guidelines on who is considered to be at increased risk of severe COVID-19 illness.6-8 This includes individuals with cardiovascular disease (CVD), chronic kidney disease (CKD), diabetes, chronic respiratory disease (CRD) and a range of other chronic conditions. Such conditions increase the risk of needing hospital-based treatment such as oxygen supplementation or mechanical ventilation. A large proportion of the additional health care burden of COVID-19 epidemics is likely to result from infection of those with underlying conditions. Identifying at-risk populations is important not only for making projections of the likely health burden in countries,9,10 but also for the design of effective strategies that aim to reduce the risk of transmission to people in target groups.
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